cuneyd/spaef: SPAEF version 1.0 with histogram match

cuneyd

Developing new metrics for spatial pattern comparison of observed and simulated variables has been planned as major part of the first work package (WP1) of the SPACE project. This goal was achieved by developing SPAtial EFficiency metric (SPAEF) described below. For that first we have extensively investigated the current state-of-art spatial comparison metrics. We tested available metrics such as coefficient of variation, correlation coefficient, Goodman and Kruskal's lambda (Goodman and Kruskal, 1954), Mapcurves (Hargrove et al., 2006), agreement coefficient (Ji and Gallo, 2006), FSS, Theil's Uncertainty, EOF and Cramér's V (Cramér, 1946; Koch et al., 2015; Rees, 2008) in calibration of a distributed hydrologic model. However, after many calibration attempts we found them inadequate due to the unexpected resultant visual patterns resulted in high correlation but too low standard deviation or highly separate groups. Therefore, we introduced a brand new multi-component SPAEF metric in Demirel et al. (2017a) which showed the utility of SPAEF in an ensemble model calibration case. For further comparison of the SPAEF with other metrics and particularly analysing each component separately in a calibration framework please refer to the subsequent study by Koch et al. (2017). Illustrative examples and source codes are available in Python 2.7 and Matlab (Demirel et al., 2017b).